From Ploomes to SQL Server: managed, scheduled, no code.
Creating a pipeline that sends data from Ploomes to SQL Server databases takes only a few minutes with Kondado. And the whole integration from Ploomes to SQL Server is managed and executed by our platform. With Kondado, you can focus on extracting value from Ploomes data and combining it with other data in your SQL Server database
Kondado enables you to replicate data from Ploomes directly into SQL Server without writing code or managing complex API connections. Our platform automates the extraction of your CRM, sales, and process automation data, loading it into your Microsoft database on a configurable schedule that fits your business needs. Whether you require near-real-time updates every five minutes or prefer daily batch processing, Kondado handles the data movement while you focus on building insights.
Once your Ploomes data lands in SQL Server, you can combine it with information from other sources like PostgreSQL or BigQuery to create comprehensive business intelligence reports. This unified approach allows analysts to query complex sales relationships, track deal progression across funnels, and generate custom dashboards that drive strategic decisions.
Kondado provides a direct integration between Ploomes and SQL Server, replicating 36 pipelines including Deals, Clients, Products, and Sales on a user-configured schedule ranging from 5 minutes to daily intervals, with no coding required.
Your Ploomes instance contains valuable sales intelligence across multiple objects that Kondado replicates into structured SQL Server tables. The Deals pipeline captures order numbers, amounts, and stage progression, enabling you to build SQL queries that analyze conversion rates and pipeline velocity directly in your database. Meanwhile, the Clients pipeline brings comprehensive company and individual data including ratings, sources, and segments, allowing you to segment your SQL analysis by customer attributes and relationship types. With the Sales and Products pipelines, you can join transaction data with inventory information to calculate margins, track bestsellers, and forecast demand using standard T-SQL commands.
Try out all the features for free for 14 days
Replicated to SQL Server
Ploomes data available for SQL Server
Tables Kondado writes into your SQL Server, on a schedule you control.
36
available pipelines
275
extractable fields
SQL Server
Destination
Available integrations
Positions
Table contains information about positions, including id, name, and associated user profile.
Cities
Table presents data about cities, including id, name, and associated state.
Cities: states
Table provides information about states related to cities, including id and state name.
Cities: countries
Table contains data about countries associated with cities, including id and country name.
Clients (companies and individuals)
Table presents information about clients, including id, name, email, and status.
Clients: ratings
Table provides data about client ratings, including id and rating name.
Clients: sources
Table contains information about client sources, including id and source name.
Clients: relationships
Table presents data about relationships between clients, including id and relationship type.
Clients: segments
Table provides information about client segments, including id and segment name.
Clients: status
Table contains data about client status, including id and status description.
Client Types
Includes fields such as id and name, allowing categorization of clients into different types for better management.
Departments
Contains fields such as id and name, facilitating the organization and structuring of departments within the company.
Documents
Presents fields such as id and filename, allowing management of documents associated with clients and sales.
Currencies
Includes fields such as id and currency, essential for financial management and conversion of values in different currencies.
Deals
Has fields such as id, ordernumber, and amount, allowing tracking and analysis of completed sales.
Deal Stages
Includes fields such as id, name, and ordination, which help define the progression of deals through different stages.
Deal Funnels
Presents fields that allow visualization and management of different sales funnels and their stages.
Deal Loss Reasons
Includes fields such as id and name, helping to identify and analyze the reasons why deals were not closed.
Deal Status
Presents fields that indicate the current status of deals, allowing better tracking of progress.
Products
Contains fields such as id and name, essential for managing and categorizing the products offered.
Product Groups
Includes fields such as id, name, and description, allowing for the categorization of products into specific groups for better organization and analysis.
Product Families
Contains fields such as id, name, and group_id, facilitating the organization of products into related families for more efficient management.
Proposals
Presents fields such as id, filename, and approval status, allowing for the management and tracking of proposals sent to clients.
Proposal Products
Includes fields such as proposal_id, product_id, and quantity, detailing the products included in each proposal for accurate tracking.
Proposal Approval Status
Contains fields such as id and name, allowing for the categorization of different approval statuses for submitted proposals.
Interaction Records
Includes fields such as id, type, and date, recording interactions made with clients for relationship analysis.
Tasks
Presents fields such as id, name, and status, allowing for effective management of tasks assigned to users within the platform.
Task Recurrence Intervals
Contains fields such as id and frequency, defining the periodicity of tasks for better work organization.
Task Types
Includes fields such as id and name, categorizing tasks into different types for easier management.
Email Reminder Types
Presents fields such as id and description, allowing the configuration of different types of email reminders for users.
Users
Table contains information about users, including fields such as id, name, and email, as well as role id and profile id.
User Suspension Reasons
Table lists the reasons for user suspension, with fields such as id and name, along with comments on the suspension.
User Profiles
Table presents user profiles, including fields such as id, name, and avatar url, along with phone and user language.
Sales
Table contains data on sales, including fields such as id, order number, date, customer id, and total sale amount.
Sales Stages
Table lists sales stages, with fields such as id, name, icon, and ordination of stages within a funnel.
Sales Products
Table contains information on sold products, including fields such as order id, product id, and quantity, along with unit price and discount.
Sync data automatically — no code, no manual exports.
1
Connect Your Ploomes Account
Authenticate your Ploomes data source in Kondado by providing your API credentials and selecting your CRM instance. The platform will automatically detect available pipelines including Deals, Clients, and Sales objects.
2
Configure SQL Server Destination
Enter your SQL Server connection details including server address, database name, and authentication credentials. Kondado validates the connection and prepares the schema to receive your Ploomes data structures.
3
Select Pipelines and Schedule
Choose which of the 36 available pipelines to replicate, such as Deals, Products, or Interaction Records, and set your preferred update frequency from 5 minutes to daily. Kondado will begin automated replication immediately, keeping your SQL Server tables current without further configuration.
Try out all the features for free for 14 days
Hundreds of data-driven companies trust Kondado
Why Kondado?
Focus on extracting value from your data and leave the rest to us
Answers about sending Ploomes data to SQL Server automatically
How does Kondado replicate Ploomes data to SQL Server?▼
Kondado connects to your Ploomes account via API and automatically extracts data from your selected pipelines. The platform then transforms and loads this information into your SQL Server instance on your chosen schedule, maintaining data relationships and field mappings without requiring manual intervention or custom development.
What Ploomes objects and fields can I replicate to SQL Server?▼
You can replicate 36 pipelines encompassing 275 fields, including Deals with order numbers and amounts, Clients with ratings and segments, Sales with transaction details, and Products with grouping and family classifications. Each pipeline corresponds to specific Ploomes entities like Deal Stages, Client Types, and Interaction Records, giving you complete access to your sales operations data.
How often does Ploomes data update in SQL Server?▼
Kondado updates your SQL Server database on a configurable schedule that you control, with options ranging from every 5 minutes for near-real-time analysis to hourly or daily intervals for batch reporting. You can adjust these frequencies per pipeline based on how current each dataset needs to be for your specific use cases.
Can I combine Ploomes data with other sources in SQL Server?▼
Yes, once your Ploomes data resides in SQL Server, you can join it with information from additional Kondado sources such as PostgreSQL, BigQuery, or Power BI exports to create unified datasets. This allows you to correlate CRM activities with financial data, marketing metrics, or inventory systems stored in the same database environment.
How is Ploomes data structured when it arrives in SQL Server?▼
Kondado creates dedicated tables for each Ploomes pipeline you select, preserving the original field names and data types from your CRM. Related entities maintain their referential integrity through foreign key relationships, allowing you to write SQL joins between tables like Deals and Deal Stages or Clients and Client Types using standard query syntax.
Can I send Ploomes data to SQL Server and other destinations simultaneously?▼
Absolutely, Kondado supports multi-destination replication, allowing you to send your Ploomes data to SQL Server while also delivering it to Google Sheets, Looker Studio, or BigQuery at the same time. This enables different teams to access the same Ploomes information through their preferred analytics tools without creating data silos.
'%3E%3Cpath d='M51,41a9.978,9.978,0,0,0-7.857,3.835L22.648,34.588a9.69,9.69,0,0,0,0-5.176l20.5-10.247a10.1,10.1,0,1,0-1.791-3.577L20.857,25.835a10,10,0,1,0,0,12.33L41.352,48.412A9.994,9.994,0,1,0,51,41Z' fill='%23383e51'%3E%3C/path%3E%3C/g%3E%3C/svg%3E)
'%3E%3Cpath d='M33,47.645V60.71c.024-.014.05-.018.073-.033l11-7A2,2,0,0,0,45,51.992V40.012Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M31,47.645,19,40.011V51.992a2,2,0,0,0,.927,1.688l11,7c.023.015.049.019.073.033Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M32,21.693l12-7.634L33.076,7.086a2,2,0,0,0-2.152,0L20,14.059Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M12,35.556,0,27.922V39.9A2,2,0,0,0,.927,41.59l11,7c.023.014.049.019.073.033Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M52,35.556l12-7.634V39.9a2,2,0,0,1-.927,1.687l-11,7c-.023.014-.049.019-.073.033Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M47,38.914a2,2,0,0,0-.924-1.686L38,32.074V27.922l12,7.634V48.621c-.024-.014-.05-.019-.073-.033L47,46.726Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M13,33.821l12-7.634L14.076,19.214a2,2,0,0,0-2.152,0L1,26.187Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M17,38.914a2,2,0,0,1,.924-1.686L26,32.074V27.922L14,35.556V48.621c.024-.014.05-.019.073-.033L17,46.726Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M32,45.91l12-7.634L33.076,31.3a2,2,0,0,0-2.152,0L20,38.276Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M14.076,19.214a2,2,0,0,0-2.152,0L1,26.187l12,7.634,12-7.634Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M49.924,19.214a2,2,0,0,1,2.152,0L63,26.187,51,33.821,39,26.187Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M26,27.922,14,35.556V48.621c.024-.014.05-.019.073-.033L17,46.726V38.914a2,2,0,0,1,.924-1.686L26,32.074Z' fill='%23383e51' data-color='color-2'%3E%3C/path%3E%3Cpath d='M27.076,25.138A2,2,0,0,1,28,26.824V30.8l1.848-1.179A4,4,0,0,1,31,29.123V23.428L19,15.794v4.19Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M36.924,25.138A2,2,0,0,0,36,26.824V30.8l-1.848-1.179A4,4,0,0,0,33,29.123V23.428l12-7.634v4.19Z' fill='%23383e51'%3E%3C/path%3E%3Cpath d='M33.076,31.3a2,2,0,0,0-2.152,0L20,38.276,32,45.91l12-7.634Z' fill='%23383e51'%3E%3C/path%3E%3C/g%3E%3C/svg%3E)
'%3E%3Cpath d='M50.348,42.573c0-9.411-8.691-12.336-16.348-14.416v-16.1a32.837,32.837,0,0,1,9.363,1.656l2.778,1.11,2.228-5.57L45.584,8.134A38.043,38.043,0,0,0,34,6.046V1H30V6.081c-8.213.594-16.348,4.86-16.348,13.471,0,9.036,8.841,11.732,16.348,13.744V50.074a33.591,33.591,0,0,1-12.006-2.511l-2.683-1.341-2.684,5.367,2.684,1.342c.243.121,5.7,2.792,14.689,3.152V63h4V56.065C44,55.462,50.348,50.3,50.348,42.573Zm-30.7-23.021c0-5.133,5.96-7.016,10.348-7.446V27.071C23.512,25.243,19.652,23.535,19.652,19.552ZM34,50.043V34.393c6.5,1.882,10.348,3.761,10.348,8.18C44.348,48.377,37.873,49.744,34,50.043Z' fill='%23383e51'%3E%3C/path%3E%3C/g%3E%3C/svg%3E)
